{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd \n",
    "import matplotlib.pyplot as plt\n",
    "import tushare as ts"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "使用tushare获取某股票的历史行情"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = ts.get_k_data('600519',start='1988-01-01')\n",
    "df.to_csv('600519.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('600519.csv', index_col='date' ,parse_dates=['date'])[['open','close','high','low']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "输出开盘比收盘上涨3%的日期"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2001-08-27</th>\n",
       "      <td>5.392</td>\n",
       "      <td>5.554</td>\n",
       "      <td>5.902</td>\n",
       "      <td>5.132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001-08-28</th>\n",
       "      <td>5.467</td>\n",
       "      <td>5.759</td>\n",
       "      <td>5.781</td>\n",
       "      <td>5.407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001-09-10</th>\n",
       "      <td>5.531</td>\n",
       "      <td>5.734</td>\n",
       "      <td>5.757</td>\n",
       "      <td>5.470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001-12-21</th>\n",
       "      <td>5.421</td>\n",
       "      <td>5.604</td>\n",
       "      <td>5.620</td>\n",
       "      <td>5.421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-18</th>\n",
       "      <td>5.437</td>\n",
       "      <td>5.726</td>\n",
       "      <td>5.762</td>\n",
       "      <td>5.421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-31</th>\n",
       "      <td>5.624</td>\n",
       "      <td>5.874</td>\n",
       "      <td>5.937</td>\n",
       "      <td>5.624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003-01-14</th>\n",
       "      <td>4.429</td>\n",
       "      <td>4.611</td>\n",
       "      <td>4.668</td>\n",
       "      <td>4.399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003-10-29</th>\n",
       "      <td>4.132</td>\n",
       "      <td>4.260</td>\n",
       "      <td>4.266</td>\n",
       "      <td>4.132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-01-05</th>\n",
       "      <td>4.862</td>\n",
       "      <td>5.114</td>\n",
       "      <td>5.124</td>\n",
       "      <td>4.862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-01-14</th>\n",
       "      <td>5.347</td>\n",
       "      <td>5.593</td>\n",
       "      <td>5.647</td>\n",
       "      <td>5.302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-01-29</th>\n",
       "      <td>5.424</td>\n",
       "      <td>5.610</td>\n",
       "      <td>5.622</td>\n",
       "      <td>5.424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-02-26</th>\n",
       "      <td>5.308</td>\n",
       "      <td>5.473</td>\n",
       "      <td>5.478</td>\n",
       "      <td>5.269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-03-02</th>\n",
       "      <td>5.463</td>\n",
       "      <td>6.031</td>\n",
       "      <td>6.079</td>\n",
       "      <td>5.463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-03-16</th>\n",
       "      <td>6.474</td>\n",
       "      <td>6.763</td>\n",
       "      <td>6.865</td>\n",
       "      <td>6.414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-03-24</th>\n",
       "      <td>6.528</td>\n",
       "      <td>6.790</td>\n",
       "      <td>6.819</td>\n",
       "      <td>6.505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-04-07</th>\n",
       "      <td>7.218</td>\n",
       "      <td>7.530</td>\n",
       "      <td>7.565</td>\n",
       "      <td>7.218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-04-08</th>\n",
       "      <td>7.536</td>\n",
       "      <td>7.842</td>\n",
       "      <td>7.850</td>\n",
       "      <td>7.501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-04-30</th>\n",
       "      <td>7.030</td>\n",
       "      <td>7.251</td>\n",
       "      <td>7.264</td>\n",
       "      <td>6.976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-05-13</th>\n",
       "      <td>7.071</td>\n",
       "      <td>7.321</td>\n",
       "      <td>7.323</td>\n",
       "      <td>7.071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-07-01</th>\n",
       "      <td>6.357</td>\n",
       "      <td>6.792</td>\n",
       "      <td>6.810</td>\n",
       "      <td>6.355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-07-05</th>\n",
       "      <td>6.860</td>\n",
       "      <td>7.198</td>\n",
       "      <td>7.211</td>\n",
       "      <td>6.860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-07-13</th>\n",
       "      <td>7.242</td>\n",
       "      <td>7.478</td>\n",
       "      <td>7.496</td>\n",
       "      <td>7.242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-07-15</th>\n",
       "      <td>7.511</td>\n",
       "      <td>7.778</td>\n",
       "      <td>7.790</td>\n",
       "      <td>7.511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-07-23</th>\n",
       "      <td>7.750</td>\n",
       "      <td>7.994</td>\n",
       "      <td>8.004</td>\n",
       "      <td>7.724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-15</th>\n",
       "      <td>7.567</td>\n",
       "      <td>7.915</td>\n",
       "      <td>7.925</td>\n",
       "      <td>7.526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-09-23</th>\n",
       "      <td>8.159</td>\n",
       "      <td>8.492</td>\n",
       "      <td>8.517</td>\n",
       "      <td>8.159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-10-19</th>\n",
       "      <td>8.842</td>\n",
       "      <td>9.142</td>\n",
       "      <td>9.198</td>\n",
       "      <td>8.817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-10-22</th>\n",
       "      <td>9.409</td>\n",
       "      <td>9.948</td>\n",
       "      <td>10.014</td>\n",
       "      <td>9.401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-11-10</th>\n",
       "      <td>9.655</td>\n",
       "      <td>10.024</td>\n",
       "      <td>10.120</td>\n",
       "      <td>9.655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-11-25</th>\n",
       "      <td>9.251</td>\n",
       "      <td>9.561</td>\n",
       "      <td>9.676</td>\n",
       "      <td>9.251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-31</th>\n",
       "      <td>728.654</td>\n",
       "      <td>753.836</td>\n",
       "      <td>760.906</td>\n",
       "      <td>728.654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-19</th>\n",
       "      <td>650.612</td>\n",
       "      <td>670.441</td>\n",
       "      <td>670.480</td>\n",
       "      <td>647.467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-07</th>\n",
       "      <td>650.711</td>\n",
       "      <td>688.396</td>\n",
       "      <td>692.054</td>\n",
       "      <td>648.561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-28</th>\n",
       "      <td>707.948</td>\n",
       "      <td>730.034</td>\n",
       "      <td>730.291</td>\n",
       "      <td>705.108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-04</th>\n",
       "      <td>741.817</td>\n",
       "      <td>771.022</td>\n",
       "      <td>771.939</td>\n",
       "      <td>735.438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-20</th>\n",
       "      <td>741.000</td>\n",
       "      <td>763.590</td>\n",
       "      <td>765.000</td>\n",
       "      <td>741.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-08-09</th>\n",
       "      <td>671.000</td>\n",
       "      <td>691.880</td>\n",
       "      <td>694.500</td>\n",
       "      <td>670.120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-08-21</th>\n",
       "      <td>647.000</td>\n",
       "      <td>671.490</td>\n",
       "      <td>672.300</td>\n",
       "      <td>647.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-08-27</th>\n",
       "      <td>662.000</td>\n",
       "      <td>687.300</td>\n",
       "      <td>687.300</td>\n",
       "      <td>662.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-09-18</th>\n",
       "      <td>643.000</td>\n",
       "      <td>666.700</td>\n",
       "      <td>668.000</td>\n",
       "      <td>642.220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-09-26</th>\n",
       "      <td>702.100</td>\n",
       "      <td>724.930</td>\n",
       "      <td>732.680</td>\n",
       "      <td>701.990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-10-19</th>\n",
       "      <td>638.000</td>\n",
       "      <td>670.000</td>\n",
       "      <td>675.000</td>\n",
       "      <td>635.080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-10-31</th>\n",
       "      <td>527.000</td>\n",
       "      <td>548.900</td>\n",
       "      <td>555.000</td>\n",
       "      <td>522.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-11-13</th>\n",
       "      <td>546.120</td>\n",
       "      <td>570.000</td>\n",
       "      <td>570.000</td>\n",
       "      <td>543.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-28</th>\n",
       "      <td>563.300</td>\n",
       "      <td>590.010</td>\n",
       "      <td>596.400</td>\n",
       "      <td>560.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-15</th>\n",
       "      <td>627.860</td>\n",
       "      <td>659.980</td>\n",
       "      <td>661.500</td>\n",
       "      <td>625.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-11</th>\n",
       "      <td>695.000</td>\n",
       "      <td>725.300</td>\n",
       "      <td>729.500</td>\n",
       "      <td>688.180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-01</th>\n",
       "      <td>761.500</td>\n",
       "      <td>789.300</td>\n",
       "      <td>790.000</td>\n",
       "      <td>761.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-18</th>\n",
       "      <td>778.800</td>\n",
       "      <td>810.090</td>\n",
       "      <td>814.530</td>\n",
       "      <td>777.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-04-10</th>\n",
       "      <td>903.000</td>\n",
       "      <td>947.990</td>\n",
       "      <td>951.900</td>\n",
       "      <td>900.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-04-16</th>\n",
       "      <td>904.900</td>\n",
       "      <td>939.900</td>\n",
       "      <td>939.900</td>\n",
       "      <td>901.220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-10</th>\n",
       "      <td>875.660</td>\n",
       "      <td>907.120</td>\n",
       "      <td>910.780</td>\n",
       "      <td>868.190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-15</th>\n",
       "      <td>890.240</td>\n",
       "      <td>927.000</td>\n",
       "      <td>933.000</td>\n",
       "      <td>890.240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-11</th>\n",
       "      <td>876.000</td>\n",
       "      <td>910.890</td>\n",
       "      <td>915.610</td>\n",
       "      <td>875.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-20</th>\n",
       "      <td>932.500</td>\n",
       "      <td>975.000</td>\n",
       "      <td>975.500</td>\n",
       "      <td>932.200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-12</th>\n",
       "      <td>1066.000</td>\n",
       "      <td>1099.000</td>\n",
       "      <td>1109.980</td>\n",
       "      <td>1066.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-18</th>\n",
       "      <td>1108.500</td>\n",
       "      <td>1148.900</td>\n",
       "      <td>1150.000</td>\n",
       "      <td>1108.180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-11</th>\n",
       "      <td>1063.000</td>\n",
       "      <td>1098.000</td>\n",
       "      <td>1099.680</td>\n",
       "      <td>1062.800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-02</th>\n",
       "      <td>1050.110</td>\n",
       "      <td>1086.010</td>\n",
       "      <td>1096.550</td>\n",
       "      <td>1050.010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-05</th>\n",
       "      <td>1136.310</td>\n",
       "      <td>1171.000</td>\n",
       "      <td>1174.990</td>\n",
       "      <td>1130.560</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>306 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                open     close      high       low\n",
       "date                                              \n",
       "2001-08-27     5.392     5.554     5.902     5.132\n",
       "2001-08-28     5.467     5.759     5.781     5.407\n",
       "2001-09-10     5.531     5.734     5.757     5.470\n",
       "2001-12-21     5.421     5.604     5.620     5.421\n",
       "2002-01-18     5.437     5.726     5.762     5.421\n",
       "2002-01-31     5.624     5.874     5.937     5.624\n",
       "2003-01-14     4.429     4.611     4.668     4.399\n",
       "2003-10-29     4.132     4.260     4.266     4.132\n",
       "2004-01-05     4.862     5.114     5.124     4.862\n",
       "2004-01-14     5.347     5.593     5.647     5.302\n",
       "2004-01-29     5.424     5.610     5.622     5.424\n",
       "2004-02-26     5.308     5.473     5.478     5.269\n",
       "2004-03-02     5.463     6.031     6.079     5.463\n",
       "2004-03-16     6.474     6.763     6.865     6.414\n",
       "2004-03-24     6.528     6.790     6.819     6.505\n",
       "2004-04-07     7.218     7.530     7.565     7.218\n",
       "2004-04-08     7.536     7.842     7.850     7.501\n",
       "2004-04-30     7.030     7.251     7.264     6.976\n",
       "2004-05-13     7.071     7.321     7.323     7.071\n",
       "2004-07-01     6.357     6.792     6.810     6.355\n",
       "2004-07-05     6.860     7.198     7.211     6.860\n",
       "2004-07-13     7.242     7.478     7.496     7.242\n",
       "2004-07-15     7.511     7.778     7.790     7.511\n",
       "2004-07-23     7.750     7.994     8.004     7.724\n",
       "2004-09-15     7.567     7.915     7.925     7.526\n",
       "2004-09-23     8.159     8.492     8.517     8.159\n",
       "2004-10-19     8.842     9.142     9.198     8.817\n",
       "2004-10-22     9.409     9.948    10.014     9.401\n",
       "2004-11-10     9.655    10.024    10.120     9.655\n",
       "2004-11-25     9.251     9.561     9.676     9.251\n",
       "...              ...       ...       ...       ...\n",
       "2018-01-31   728.654   753.836   760.906   728.654\n",
       "2018-04-19   650.612   670.441   670.480   647.467\n",
       "2018-05-07   650.711   688.396   692.054   648.561\n",
       "2018-05-28   707.948   730.034   730.291   705.108\n",
       "2018-06-04   741.817   771.022   771.939   735.438\n",
       "2018-06-20   741.000   763.590   765.000   741.000\n",
       "2018-08-09   671.000   691.880   694.500   670.120\n",
       "2018-08-21   647.000   671.490   672.300   647.000\n",
       "2018-08-27   662.000   687.300   687.300   662.000\n",
       "2018-09-18   643.000   666.700   668.000   642.220\n",
       "2018-09-26   702.100   724.930   732.680   701.990\n",
       "2018-10-19   638.000   670.000   675.000   635.080\n",
       "2018-10-31   527.000   548.900   555.000   522.000\n",
       "2018-11-13   546.120   570.000   570.000   543.000\n",
       "2018-12-28   563.300   590.010   596.400   560.000\n",
       "2019-01-15   627.860   659.980   661.500   625.000\n",
       "2019-02-11   695.000   725.300   729.500   688.180\n",
       "2019-03-01   761.500   789.300   790.000   761.000\n",
       "2019-03-18   778.800   810.090   814.530   777.000\n",
       "2019-04-10   903.000   947.990   951.900   900.000\n",
       "2019-04-16   904.900   939.900   939.900   901.220\n",
       "2019-05-10   875.660   907.120   910.780   868.190\n",
       "2019-05-15   890.240   927.000   933.000   890.240\n",
       "2019-06-11   876.000   910.890   915.610   875.000\n",
       "2019-06-20   932.500   975.000   975.500   932.200\n",
       "2019-09-12  1066.000  1099.000  1109.980  1066.000\n",
       "2019-09-18  1108.500  1148.900  1150.000  1108.180\n",
       "2020-02-11  1063.000  1098.000  1099.680  1062.800\n",
       "2020-03-02  1050.110  1086.010  1096.550  1050.010\n",
       "2020-03-05  1136.310  1171.000  1174.990  1130.560\n",
       "\n",
       "[306 rows x 4 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['close']-df['open'])/df['open']>=0.03]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "开盘比前日收盘上涨2%的日期"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['rate'] = (df['open'].shift(-1)-df['close'])/df['close']\n",
    "#df[df['rate']>=0.02].index\n",
    "#df[df['rate']>=0.02]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从2010-01-01开始每月第一个交易日买入一手股票，每年最后一个交易日卖出全部股票，到今天能挣多少钱"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df['2001-09':'2020-02']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_monthly = df.resample('m').first()\n",
    "df_yearly = df.resample('a').last()[:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "cost_money = 0\n",
    "hold = 0\n",
    "for year in range(2001,2021):\n",
    "    cost_money-=df_monthly[str(year)]['open'].sum()*100\n",
    "    hold = len(df_monthly[str(year)])*100\n",
    "    if year != 2020:\n",
    "        cost_money+=df_yearly[str(year)]['close'][0]*hold\n",
    "    else: cost_money+=df_monthly[str(year)]['close'][-1]*hold\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "687291.4999999998"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cost_money"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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